bayesplot.R

# c('practicality', 'difficulty', 'some color, dunno')

papers <- rbind(
# paper we discuss
c(5, 3, 1), # Lindley (1993)
c(8, 0, 1), # Kruschke (2010)
c(4, 3, 1), # Wagenmakers (2007)
c(5, 2, 1), # Dienes (2011)
c(3, 7, 1), # Vandekerckhove, Matzke, Wagenmakers (2015)
c(4, 8, 1), # Rouder & Morey (2012)
c(7, 1, 1), # Gallistel (2009)
c(7, 4, 1), # van de Schoot (2013)
c(6, 3, 1), # Lee & Vanpaemel (this issue)
c(5, 5, 1), # Lee (2008)
# ----------
  
# further reading [theoretical]
c(1, 8, 0), # Edwards, Lindman, Savage (1963)
c(2, 8, 0), # Ly, Verhagen, Wagenmakers (in press)
c(1, 10, 0), # Berger & Delampardy (1987)
c(7, 2, 0), # Wetzels et al. (2011)
c(3, 8, 0), # Vanpaemel (2010)
c(6, 1, 0), # Cornfield (1966)
c(2, 2, 0), # Jaynes (1986)
c(2, 6, 0), # Royall (2004)
c(1, 9, 0), # Jeffreys (1936)
# ----------
  
# further reading [practical]
c(1, 7, 0), # Wagenmakers, Morey, Lee (under revision)
c(10, 7, 0), # Lee & Wagenmakers (2014)
c(9, 6, 0), # Wagenmakers et al. (2010)
c(7, 7, 0), # Rouder & Lu (2005)
c(3, 3, 0), # Schönbrodt et al. (in press)
c(8, 4, 0) # Sorensen & Vasishth (submitted)
)


values <- papers[, 1:2]
color <- ifelse(papers[, 3], 'red', 'black')

op <- par(cex.main = 1.2, mar = c(5, 6, 4, 5) + 0.1, mgp = c(3.5, 1, 0),
          cex.lab = 1.2 , font.lab = 2, cex.axis = 1.3, bty = "n", las = 1)

plot(values, xlab = 'practicality', ylab = 'difficulty', cex = 1.7,
     pch = 21, bg = color, xlim = c(0, 10), ylim = c(0, 10), type = 'n')

abline(v = 5, lty = 2, lwd = 1.4, col = 'grey50')
abline(h = 5, lty = 2, lwd = 1.4, col = 'grey50')

title('Overview of papers')
axis(1, at = 0:10)
axis(2, at = 0:10)

labels <- as.character(seq_len(nrow(papers)))
offset <- ifelse(labels %in% 1:9, .16, .2)
text(values, labels = seq_len(nrow(papers)), col = color)